Pandas Profiling Report

Dataset statistics

Number of variables	10
Number of observations	25751
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	3.1 MiB
Average record size in memory	125.0 B

Variable types

Numeric	8
Categorical	2

Alerts

`alert_key` is highly correlated with `date`	High correlation
`date` is highly correlated with `alert_key`	High correlation
`tx_time` is highly correlated with `amt`	High correlation
`amt` is highly correlated with `tx_time`	High correlation
`amt` is highly skewed (γ1 = 82.57466783)	Skewed
`alert_key` has unique values	Unique
`total_asset` has 3120 (12.1%) zeros	Zeros
`tx_time` has 8142 (31.6%) zeros	Zeros
`amt` has 6043 (23.5%) zeros	Zeros

Reproduction

Analysis started	2022-12-17 15:11:37.165880
Analysis finished	2022-12-17 15:12:01.738154
Duration	24.57 seconds
Software version	pandas-profiling v3.4.0
Download configuration	config.json

alert_key
Real number (ℝ_≥0)

HIGH CORRELATION
UNIQUE

Distinct	25751
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	265685.6269

Minimum	171142
Maximum	365073
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	402.4 KiB

Quantile statistics

Minimum	171142
5-th percentile	176967.5
Q1	212536
median	266346
Q3	316658.5
95-th percentile	356314.5
Maximum	365073
Range	193931
Interquartile range (IQR)	104122.5

Descriptive statistics

Standard deviation	58623.84087
Coefficient of variation (CV)	0.2206511566
Kurtosis	-1.273665901
Mean	265685.6269
Median Absolute Deviation (MAD)	51941
Skewness	-0.008439744393
Sum	6841670579
Variance	3436754718
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
352249	1	< 0.1%
288385	1	< 0.1%
288417	1	< 0.1%
288413	1	< 0.1%
288404	1	< 0.1%
288403	1	< 0.1%
288401	1	< 0.1%
288399	1	< 0.1%
288397	1	< 0.1%
288395	1	< 0.1%
Other values (25741)	25741	> 99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
171142	1	< 0.1%
171152	1	< 0.1%
171177	1	< 0.1%
171178	1	< 0.1%
171180	1	< 0.1%
171181	1	< 0.1%
171189	1	< 0.1%
171192	1	< 0.1%
171197	1	< 0.1%
171200	1	< 0.1%

Value	Count	Frequency (%)
365073	1	< 0.1%
365009	1	< 0.1%
365008	1	< 0.1%
365004	1	< 0.1%
365001	1	< 0.1%
364999	1	< 0.1%
364996	1	< 0.1%
364995	1	< 0.1%
364994	1	< 0.1%
364993	1	< 0.1%

cust_id
Real number (ℝ_≥0)

Distinct	7708
Distinct (%)	29.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3694.211137

Minimum	0
Maximum	7707
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	301.8 KiB

Quantile statistics

Minimum	0
5-th percentile	268.5
Q1	1761
median	3685
Q3	5489
95-th percentile	7291
Maximum	7707
Range	7707
Interquartile range (IQR)	3728

Descriptive statistics

Standard deviation	2226.914988
Coefficient of variation (CV)	0.6028120498
Kurtosis	-1.144245677
Mean	3694.211137
Median Absolute Deviation (MAD)	1838
Skewness	0.05270535689
Sum	95129631
Variance	4959150.364
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
120	246	1.0%
540	164	0.6%
255	158	0.6%
2779	150	0.6%
7637	142	0.6%
1179	141	0.5%
3782	131	0.5%
1898	118	0.5%
272	118	0.5%
1057	117	0.5%
Other values (7698)	24266	94.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	3	< 0.1%
3	4	< 0.1%
4	6	< 0.1%
5	43	0.2%
6	1	< 0.1%
7	1	< 0.1%
8	12	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
7707	1	< 0.1%
7706	3	< 0.1%
7705	1	< 0.1%
7704	30	0.1%
7703	1	< 0.1%
7702	1	< 0.1%
7701	1	< 0.1%
7700	1	< 0.1%
7699	1	< 0.1%
7698	1	< 0.1%

risk_rank
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	402.4 KiB

1	17348
3	7448
2	891
0	64

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	25751
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	3
5th row	1

Common Values

Value	Count	Frequency (%)
1	17348	67.4%
3	7448	28.9%
2	891	3.5%
0	64	0.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	17348	67.4%
3	7448	28.9%
2	891	3.5%
0	64	0.2%

Most occurring characters

Value	Count	Frequency (%)
1	17348	67.4%
3	7448	28.9%
2	891	3.5%
0	64	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	25751	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	17348	67.4%
3	7448	28.9%
2	891	3.5%
0	64	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	25751	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	17348	67.4%
3	7448	28.9%
2	891	3.5%
0	64	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	25751	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	17348	67.4%
3	7448	28.9%
2	891	3.5%
0	64	0.2%

occupation_code
Real number (ℝ_≥0)

Distinct	21
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14.18686653

Minimum	0
Maximum	20
Zeros	118
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	402.4 KiB

Quantile statistics

Minimum	0
5-th percentile	4
Q1	12
median	15
Q3	19
95-th percentile	19
Maximum	20
Range	20
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	4.775775434
Coefficient of variation (CV)	0.3366335635
Kurtosis	-0.08229778166
Mean	14.18686653
Median Absolute Deviation (MAD)	3
Skewness	-0.8265953145
Sum	365326
Variance	22.808031
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
19	6305	24.5%
12	5047	19.6%
17	4110	16.0%
9	2464	9.6%
18	1236	4.8%
15	1006	3.9%
13	979	3.8%
5	946	3.7%
20	704	2.7%
14	635	2.5%
Other values (11)	2319	9.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	118	0.5%
1	220	0.9%
2	130	0.5%
3	314	1.2%
4	555	2.2%
5	946	3.7%
6	1	< 0.1%
7	103	0.4%
8	135	0.5%
9	2464	9.6%

Value	Count	Frequency (%)
20	704	2.7%
19	6305	24.5%
18	1236	4.8%
17	4110	16.0%
16	321	1.2%
15	1006	3.9%
14	635	2.5%
13	979	3.8%
12	5047	19.6%
11	351	1.4%

total_asset
Real number (ℝ_≥0)

ZEROS

Distinct	8073
Distinct (%)	31.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	713742.6661

Minimum	0
Maximum	73863211
Zeros	3120
Zeros (%)	12.1%
Negative	0
Negative (%)	0.0%
Memory size	402.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	7508
median	128880
Q3	597231.5
95-th percentile	2717416
Maximum	73863211
Range	73863211
Interquartile range (IQR)	589723.5

Descriptive statistics

Standard deviation	2435460.555
Coefficient of variation (CV)	3.412238991
Kurtosis	231.2987476
Mean	713742.6661
Median Absolute Deviation (MAD)	128880
Skewness	12.73843401
Sum	1.83795874 × 10¹⁰
Variance	5.931468114 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3120	12.1%
101	145	0.6%
303	83	0.3%
715	79	0.3%
104	76	0.3%
8848	73	0.3%
102	51	0.2%
103	40	0.2%
18390	32	0.1%
201	30	0.1%
Other values (8063)	22022	85.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	3120	12.1%
6	5	< 0.1%
7	1	< 0.1%
14	5	< 0.1%
16	6	< 0.1%
22	1	< 0.1%
24	2	< 0.1%
26	1	< 0.1%
30	3	< 0.1%
31	1	< 0.1%

Value	Count	Frequency (%)
73863211	1	< 0.1%
54967807	1	< 0.1%
54497222	11	< 0.1%
54352277	1	< 0.1%
47869576	5	< 0.1%
47223161	1	< 0.1%
43169799	1	< 0.1%
38202504	1	< 0.1%
37641013	4	< 0.1%
35829293	5	< 0.1%

AGE
Real number (ℝ_≥0)

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.63302396

Minimum	0
Maximum	10
Zeros	3
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	402.4 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	3
median	3
Q3	4
95-th percentile	6
Maximum	10
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.309948141
Coefficient of variation (CV)	0.3605668874
Kurtosis	0.6346197153
Mean	3.63302396
Median Absolute Deviation (MAD)	1
Skewness	0.7775862555
Sum	93554
Variance	1.715964133
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
3	8165	31.7%
4	6498	25.2%
2	5088	19.8%
5	3531	13.7%
6	1725	6.7%
7	479	1.9%
1	93	0.4%
8	88	0.3%
9	74	0.3%
10	7	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	3	< 0.1%
1	93	0.4%
2	5088	19.8%
3	8165	31.7%
4	6498	25.2%
5	3531	13.7%
6	1725	6.7%
7	479	1.9%
8	88	0.3%
9	74	0.3%

Value	Count	Frequency (%)
10	7	< 0.1%
9	74	0.3%
8	88	0.3%
7	479	1.9%
6	1725	6.7%
5	3531	13.7%
4	6498	25.2%
3	8165	31.7%
2	5088	19.8%
1	93	0.4%

date
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	262
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	198.1640325

Minimum	0
Maximum	393
Zeros	88
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	402.4 KiB

Quantile statistics

Minimum	0
5-th percentile	11
Q1	92
median	210
Q3	295
95-th percentile	376
Maximum	393
Range	393
Interquartile range (IQR)	203

Descriptive statistics

Standard deviation	118.263229
Coefficient of variation (CV)	0.596794623
Kurtosis	-1.242200673
Mean	198.1640325
Median Absolute Deviation (MAD)	102
Skewness	-0.1382121659
Sum	5102922
Variance	13986.19134
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11	1010	3.9%
13	410	1.6%
272	255	1.0%
273	239	0.9%
277	215	0.8%
280	203	0.8%
377	186	0.7%
312	182	0.7%
6	177	0.7%
258	161	0.6%
Other values (252)	22713	88.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	88	0.3%
5	152	0.6%
6	177	0.7%
7	83	0.3%
8	86	0.3%
11	1010	3.9%
12	84	0.3%
13	410	1.6%
14	94	0.4%
15	67	0.3%

Value	Count	Frequency (%)
393	102	0.4%
392	79	0.3%
391	76	0.3%
390	77	0.3%
389	99	0.4%
386	89	0.3%
385	66	0.3%
384	66	0.3%
383	90	0.3%
382	104	0.4%

tx_time
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	257
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.896081706

Minimum	0
Maximum	479
Zeros	8142
Zeros (%)	31.6%
Negative	0
Negative (%)	0.0%
Memory size	402.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	3
Q3	6
95-th percentile	17
Maximum	479
Range	479
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	27.30572394
Coefficient of variation (CV)	3.959599828
Kurtosis	136.9119409
Mean	6.896081706
Median Absolute Deviation (MAD)	3
Skewness	11.00664706
Sum	177581
Variance	745.6025598
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	8142	31.6%
1	2395	9.3%
2	2279	8.9%
5	2003	7.8%
3	1918	7.4%
4	1759	6.8%
6	1570	6.1%
7	1097	4.3%
8	864	3.4%
9	582	2.3%
Other values (247)	3142	12.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	8142	31.6%
1	2395	9.3%
2	2279	8.9%
3	1918	7.4%
4	1759	6.8%
5	2003	7.8%
6	1570	6.1%
7	1097	4.3%
8	864	3.4%
9	582	2.3%

Value	Count	Frequency (%)
479	1	< 0.1%
450	1	< 0.1%
446	1	< 0.1%
443	1	< 0.1%
439	2	< 0.1%
438	1	< 0.1%
431	1	< 0.1%
430	1	< 0.1%
425	1	< 0.1%
424	1	< 0.1%

amt
Real number (ℝ)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	18497
Distinct (%)	71.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5770835.038

Minimum	-88663278.2
Maximum	9364465262
Zeros	6043
Zeros (%)	23.5%
Negative	2
Negative (%)	< 0.1%
Memory size	402.4 KiB

Quantile statistics

Minimum	-88663278.2
5-th percentile	0
Q1	173.5
median	66926.02
Q3	778552.6175
95-th percentile	18359600.9
Maximum	9364465262
Range	9453128541
Interquartile range (IQR)	778379.1175

Descriptive statistics

Standard deviation	92210705.88
Coefficient of variation (CV)	15.97874576
Kurtosis	8073.687761
Mean	5770835.038
Median Absolute Deviation (MAD)	66926.02
Skewness	82.57466783
Sum	1.486047731 × 10¹¹
Variance	8.50281428 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6043	23.5%
4	26	0.1%
8	15	0.1%
1031	13	0.1%
20	11	< 0.1%
12	10	< 0.1%
1	9	< 0.1%
17	8	< 0.1%
1043	8	< 0.1%
516	7	< 0.1%
Other values (18487)	19601	76.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-88663278.2	1	< 0.1%
-997441	1	< 0.1%
0	6043	23.5%
1	9	< 0.1%
2	4	< 0.1%
3	7	< 0.1%
4	26	0.1%
5	7	< 0.1%
6	4	< 0.1%
7	4	< 0.1%

Value	Count	Frequency (%)
9364465262	1	< 0.1%
9233717521	1	< 0.1%
2440307900	1	< 0.1%
2381178463	1	< 0.1%
1569323372	1	< 0.1%
1566106409	1	< 0.1%
1521121594	1	< 0.1%
1498621080	1	< 0.1%
1445719427	1	< 0.1%
1381436111	1	< 0.1%

sar_flag
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	402.4 KiB

0.0	25517
1.0	234

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	77253
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	25517	99.1%
1.0	234	0.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0.0	25517	99.1%
1.0	234	0.9%

Most occurring characters

Value	Count	Frequency (%)
0	51268	66.4%
.	25751	33.3%
1	234	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	51502	66.7%
Other Punctuation	25751	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	51268	99.5%
1	234	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	25751	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	77253	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	51268	66.4%
.	25751	33.3%
1	234	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	77253	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	51268	66.4%
.	25751	33.3%
1	234	0.3%

Auto

The auto setting is an easily interpretable pairwise column metric of the following mapping: vartype-vartype : method, categorical-categorical : Cramer's V, numerical-categorical : Cramer's V (using a discretized numerical column), numerical-numerical : Spearman's ρ. This configuration uses the best suitable for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	alert_key	cust_id	risk_rank	occupation_code	total_asset	AGE	date	tx_time	amt
0	352249	3912	1	19.0	1465816.0	7	365	24.0	1.286508e+07
1	352253	5393	1	2.0	98177.0	2	365	5.0	2.054065e+07
2	352254	6924	1	19.0	2052922.0	7	365	13.0	1.394017e+06
3	352280	3431	3	15.0	201906.0	5	365	13.0	6.514627e+06
4	352282	84	1	12.0	7450.0	5	365	1.0	1.047400e+04
5	352291	3932	1	17.0	182242.0	5	365	3.0	2.320450e+05
6	352298	7637	3	12.0	2422.0	4	365	4.0	3.339420e+05
7	352301	1317	1	19.0	2536600.0	4	365	1.0	2.647000e+03
8	352302	4769	1	17.0	173255.0	4	365	4.0	8.643975e+05
9	352305	4063	3	12.0	876408.0	3	365	13.0	1.560263e+07

Last rows

	alert_key	cust_id	risk_rank	occupation_code	total_asset	AGE	date	tx_time	amt
25741	352111	3066	1	17.0	829412.0	6	364	10.0	169170.000
25742	352114	5997	1	2.0	444392.0	3	364	6.0	829302.045
25743	352118	5306	1	15.0	242106.0	4	364	5.0	50632.185
25744	352119	7209	1	13.0	40907.0	2	364	1.0	13719.000
25745	352120	3910	1	17.0	114439.0	2	364	6.0	4251483.815
25746	352123	5500	1	17.0	12207.0	2	364	1.0	176612.000
25747	352124	188	1	17.0	259985.0	4	364	1.0	49784.000
25748	352125	336	3	19.0	928963.0	3	364	1.0	6900402.000
25749	352128	7704	3	19.0	21647.0	4	364	3.0	15680.000
25750	352132	5923	1	19.0	3218731.0	3	364	2.0	2837081.916

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Auto

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows